The start of the 21st century marks a watershed in the biological sciences. In the past, the diversity of organisms bred a divergent range of academic disciplines, each with its own factual universe, world-view and educational culture. Today, the biological sciences are converging as biology undergoes a "grand unification" based on the evident similarities, across all biota, of the structures and functions of the molecules that perform virtually all basic functions.
The rapidly increasing role of quantitative concepts and computation in biology, based on genomic sequences and imaging (both molecular and cellular), is equally dramatic. Our ability to collect data has been growing exponentially, just about keeping pace with Moore's law, which famously describes the exponential increase in the productivity of computers with time.
Along with this challenge comes an equally impressive opportunity: our burgeoning ability to collect detailed and comprehensive data will facilitate, often for the first time, the derivation of realistic and predictive quantitative models for many diverse and increasingly complex biological systems and phenomena. Only when the behavior of these biological systems can be quantitatively predicted, even if only on a probabilistic basis, will we be able to say that we truly understand them. In this way, biology is being transformed, day by day, into an information science.
The primary goal of the Lewis-Sigler Institute is to foster research and teaching at Princeton that fully meets the challenges and opportunities presented by the new quantitative sciences. The Institute aims to increase communication among researchers from different disciplines and departments, and our resident faculty already represent Chemistry, Molecular Biology, Computer Science, Chemical Engineering and Physics. The research programs of the faculty, though diverse, share the idea that the tools of genomics and other new informational technologies can be focused on specific biological systems or phenomena. This focus will elicit information, we hope, that can then be used to derive quantitative models that allow prediction of salient biological properties. The predictions can be tested using the same array of technologies, providing a process of experiment and theory that will lead to better and deeper understanding of biological systems.
For both undergraduate and graduate students, the Institute provides a new environment where the quantitative and biological are integrated from the beginning. The goal is to provide not only a research environment but also an education that prepares students with equal facility in biological and quantitative concepts.